Operator-ready prompt for reuse, tuning, and workspace runs.
This item is set up for developers who want to inspect the original language, fork it into Workspace, and adapt the evidence model without losing the source prompt structure.
Implementation handoffs, eval setup, and prompt tuning where you need the original structure intact.
Inspect first, copy once, then fork into Workspace when you want variants, notes, and model settings attached to the same run.
Swap domain facts, examples, and any hard-coded entities for your own context.
Tighten the evidence or verification requirement if this is headed toward production.
Decide which failure mode you want to evaluate first before you branch the prompt.
This prompt already carries implementation detail, tool context, and a final-output instruction. Keep that structure intact when you tune it, or your comparison runs get noisy fast.
Open this prompt inside Workspace when you want a live iteration loop.
Copy for quick reuse, or run it in Workspace to keep prompt variants, model settings, and prompt-history changes in one place.
Structured source with 1 active lines to adapt.
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Prompt content
Original prompt text with formatting preserved for inspection and clean copy.
Using Mastra AI, initialize a new `Workflow` named 'ArcticSentinel'. Define a starting step that triggers when a 'SensorAlert' is received. Import `{ Mastra, Agent, Workflow } from '@mastra/core'`. Define a tool `calculateIntercept` that takes GPS coordinates and returns a vector. Ensure the workflow state maintains the history of 'LastKnownIcePosition'.Adaptation plan
Keep the source stable, then branch your edits in a predictable order so the next prompt run is easier to evaluate.
Hold the task contract and output shape stable so generated implementations remain comparable.
Update libraries, interfaces, and environment assumptions to match the stack you actually run.
Test failure handling, edge cases, and any code paths that depend on hidden context or secrets.
Copy once for a pristine source snapshot, then move the prompt into Workspace when you want variants, run history, and side-by-side tuning without losing the original.
Prompt diagnostics
Quick signals for how structured this prompt already is and where adaptation work is likely to happen first.
This prompt is mostly narrative and instruction-driven, so you can adapt examples and output constraints first without disturbing the structure.
Arctic Sentinel: Agentic Swarm Orchestration with Mastra AI and Haize Labs
Inspired by recent defense directives highlighting unmanned systems as the linchpin of Arctic maritime defense, this challenge tasks you with building a resilient multi-agent orchestration layer. You will develop a system capable of managing a swarm of Unmanned Underwater Vehicles (UUVs) and Unmanned Surface Vessels (USVs) in a simulated Arctic environment. The core focus is on maintaining surveillance persistence despite high-latency communication and adversarial interference. Using the Mastra AI framework, you will design 'Agentic Workflows' that handle sensor fusion from sonar and AIS (Automatic Identification System) data. To ensure the robustness of the mission logic against 'chilling' tactical failures or adversarial data poisoning, you will integrate Haize Labs for automated red-teaming and safety evaluation. The system must autonomously re-route patrol paths when a primary node fails or when ice shelf telemetry suggests a navigation hazard, all while keeping the 'Information Dominance' objectives of Zero Trust architecture in mind.
Use the challenge page to recover the original task boundaries before you tune the prompt. That keeps your variants grounded in the same evaluation target instead of drifting into a different problem.